linreg-core 0.8.1

Lightweight regression library (OLS, Ridge, Lasso, Elastic Net, WLS, LOESS, Polynomial) with 14 diagnostic tests, cross validation, and prediction intervals. Pure Rust - no external math dependencies. WASM, Python, FFI, and Excel XLL bindings.
Documentation
{
  "test_name": "DFBETAS (Python - statsmodels)",
  "dataset": "ToothGrowth",
  "formula": "len ~ supp + dose",
  "dfbetas": [
    [
      -0.34717241937119186,
      0.203547873399333,
      0.217601829733347
    ],
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      -0.035661160050884294
    ],
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      0.10108424264120486,
      0.1080636009042535
    ],
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      0.15007343873498574,
      0.1604352544575144
    ],
    [
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      0.13036791736789263,
      0.13936916600511023
    ],
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      0.015485048396180107
    ],
    [
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      -0.0254234421429114
    ],
    [
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      -0.0254234421429114
    ],
    [
      -0.2898746027019059,
      0.1699540506106948,
      0.1816885225370394
    ],
    [
      -0.18900299904943882,
      0.11081283067441973,
      0.1184638989835015
    ],
    [
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      -0.00974078515182002
    ],
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      -0.00974078515182002
    ],
    [
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      0.004257988568250978,
      0.001137995312800164
    ],
    [
      0.06563988970934016,
      -0.06157567463315555,
      -0.016456791274054024
    ],
    [
      0.2454345372710965,
      -0.23023800432426852,
      -0.06153369497114396
    ],
    [
      0.06563988970934016,
      -0.06157567463315555,
      -0.016456791274054024
    ],
    [
      -0.057999421530470725,
      0.0544082801614297,
      0.014541224526261885
    ],
    [
      -0.027899044151806954,
      0.026171623274724658,
      0.006994660539265084
    ],
    [
      0.11625626980323091,
      -0.10905804801267681,
      -0.0291469893524136
    ],
    [
      0.005468304664407572,
      -0.005129724475495319,
      -0.0013709765339900836
    ],
    [
      0.010322061379016876,
      0.04841475936600189,
      -0.06469694357525423
    ],
    [
      0.04644001179976163,
      0.21782296323198552,
      -0.2910781783521325
    ],
    [
      -0.06310629012302478,
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      0.39553960603568955
    ],
    [
      -0.002752657453005051,
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      0.01725319365770911
    ],
    [
      -0.00894776368074128,
      -0.04196873178332138,
      0.05608307688949178
    ],
    [
      -0.05239657207941708,
      -0.24576170744202383,
      0.3284128957273542
    ],
    [
      -0.01101707867061908,
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      0.06905319499126694
    ],
    [
      0.02491636153313543,
      0.11686809481247912,
      -0.15617156079761718
    ],
    [
      0.012393384073012602,
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      -0.07767964562855456
    ],
    [
      -0.030562576478569296,
      -0.14335119037588703,
      0.1915610858474127
    ],
    [
      0.028447764496328676,
      0.033357960731302365,
      -0.03566116005088429
    ],
    [
      0.2055255296022832,
      0.24100004577312334,
      -0.25763988613713373
    ],
    [
      0.09426409194482804,
      0.11053444561083903,
      -0.11816629283224664
    ],
    [
      -0.12236588146142785,
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      0.15339375029369873
    ],
    [
      0.00940013352986458,
      0.011022633613201388,
      -0.011783690994467457
    ],
    [
      -0.11396948749046296,
      -0.1336410700660971,
      0.14286831342545234
    ],
    [
      -0.16493527918469478,
      -0.19340375820972314,
      0.2067573144386128
    ],
    [
      -0.13079781622140352,
      -0.15337403463886884,
      0.16396373989878335
    ],
    [
      0.06395899018206853,
      0.0749985638830629,
      -0.08017683730017049
    ],
    [
      -0.12236588146142785,
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      0.15339375029369873
    ],
    [
      0.004430374804803234,
      0.020780299806347973,
      -0.00555376873356453
    ],
    [
      0.028712319923042566,
      0.13467271786810672,
      -0.035992797829160574
    ],
    [
      0.030774531658009176,
      0.1443453482898877,
      -0.03857791704824457
    ],
    [
      0.05053580270223756,
      0.23703392542988014,
      -0.0633499812857742
    ],
    [
      0.006433857721097442,
      0.030177467651472126,
      -0.008065267482312845
    ],
    [
      0.041937410259458706,
      0.19670389000711594,
      -0.052571325932313846
    ],
    [
      0.04620880066975154,
      0.21673848690391279,
      -0.05792579718016668
    ],
    [
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      0.0678748348087919,
      -0.01814031264560513
    ],
    [
      -0.03058268041012171,
      -0.14344548617330008,
      0.038337418781400644
    ],
    [
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      -0.0716344335745969
    ],
    [
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      -0.1429994693560553
    ],
    [
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      -0.07761314980424633,
      -0.10371493402707399
    ],
    [
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      -0.28185677719285857
    ],
    [
      0.1492456977407295,
      -0.14000487455380933,
      -0.18708938323520521
    ],
    [
      0.1386487558064253,
      -0.13006406186288955,
      -0.17380541350823553
    ],
    [
      -0.07236584234836432,
      0.06788517748471783,
      0.0907153842100693
    ],
    [
      0.08273589568438589,
      -0.07761314980424633,
      -0.10371493402707399
    ],
    [
      0.05161030689506787,
      -0.04841475936600672,
      -0.06469694357523612
    ],
    [
      -0.020640948571390826,
      0.019362926095375023,
      0.02587479837655636
    ],
    [
      0.2029553095022624,
      -0.1903889564458677,
      -0.2544179447306516
    ]
  ],
  "n": 60,
  "p": 3,
  "threshold": 0.2581988897471611,
  "influential_observations": [
    1,
    9,
    22,
    23,
    26,
    50,
    53
  ],
  "description": "Measures influence of each observation on each regression coefficient."
}